Still not sold on foldable smartphones? But companies continue their efforts to make them happen, with Oppo the latest to reveal its first take on a foldable flagship. It has a different screen ratio to devices from Samsung and the rest, resulting in a more horizontal (possibly more useful) touchscreen. Engadget Chinese Editor-in-Chief Richard Lai is testing one out -- expect to hear our full verdict soon. The US government is adding eight Chinese companies, including drone manufacturer DJI, to an investment blocklist for alleged involvement in the surveillance of Uyghur Muslims.

In his 2021 Reith lectures, the third episode of which airs tonight, the artificial intelligence researcher Stuart Russell takes up the idea of a near-future AI that is so ruthlessly intelligent that it might pose an existential threat to humanity. A machine we create that might destroy us all. This has long been a popular topic with researchers and the press. But we believe an existential threat from AI is both unlikely and in any case far off, given the current state of the technology. However, the recent development of powerful, but far smaller-scale, AI systems has had a significant effect on the world already, and the use of existing AI poses serious economic and social challenges.

We put together a history of artists working with artificial intelligence and key developments in the field today.

As a result, all major cloud providers are either offering or promising to offer Kubernetes options that run on-premises and in multiple clouds. While Kubernetes is making the cloud more open, cloud providers are trying to become "stickier" with more vertical integration. From database-as-a-service (DBaaS) to AI/ML services, the cloud providers are offering options that make it easier and faster to code. Organizations should not take a "one size fits all" approach to the cloud. For applications and environments that can scale quickly, Kubernetes may be the right option. For stable applications, leveraging DBaaS and built-in AI/ML could be the perfect solution. For infrastructure services, SaaS offerings may be the optimal approach. The number of options will increase, so create basic business guidelines for your teams.

Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge. Existing 3D GANs are either compute-intensive or make approximations that are not 3D-consistent; the former limits quality and resolution of the generated images and the latter adversely affects multi-view consistency and shape quality. In this work, we improve the computational efficiency and image quality of 3D GANs without overly relying on these approximations. For this purpose, we introduce an expressive hybrid explicit-implicit network architecture that, together with other design choices, synthesizes not only high-resolution multi-view-consistent images in real time but also produces high-quality 3D geometry. By decoupling feature generation and neural rendering, our framework is able to leverage state-of-the-art 2D CNN generators, such as StyleGAN2, and inherit their efficiency and expressiveness.

AI is being applied to whale research, especially to understand what whales are trying to communicate in the audible sounds they make to each other in the ocean. For example, marine biologist Shane Gero has worked to match clicks coming from whales around the Caribbean island nation of Dominica, to behavior he hopes will reveal the meanings of the sounds they make. Gero is a behavioral ecologist affiliated with the Marine Bioacoustics Lab at Aarhus University in Denmark, and the Department of Biology of Dalhousie University of Halifax, Nova Scotia. Gero works with a team from Project CETI, a nonprofit that aims to apply advanced machine learning and state-of-the-art robotics to listen to and translate the communication of whales. Project CETI has recently announced a five-year effort to build on Gero's work with a research project to try to decipher what sperm whales are saying to each other, according to a recent account in National Geographic.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The U.S. military downed a drone deemed to have hostile intent Tuesday that was headed toward a base in southeast Syria that houses 200 American troops, a senior defense official told Fox News' Jennifer Griffin. Two unmanned aerial systems were spotted entering the At Tanf Garrison Deconfliction Zone located along the Iraq and Jordan-Syria border. One of the two drones traveled deeper into the zone and was shot down after "demonstrating hostile intent," Capt.

Artificial intelligence (AI) models that evaluate medical images have potential to speed up and improve accuracy of cancer diagnoses, but they may also be vulnerable to cyberattacks. In a new study, University of Pittsburgh researchers simulated an attack that falsified mammogram images, fooling both an AI breast cancer diagnosis model and human breast imaging radiologist experts. The study, published today in Nature Communications, brings attention to a potential safety issue for medical AI known as "adversarial attacks," which seek to alter images or other inputs to make models arrive at incorrect conclusions. "What we want to show with this study is that this type of attack is possible, and it could lead AI models to make the wrong diagnosis -- which is a big patient safety issue," said senior author Shandong Wu, Ph.D., associate professor of radiology, biomedical informatics and bioengineering at Pitt. "By understanding how AI models behave under adversarial attacks in medical contexts, we can start thinking about ways to make these models safer and more robust." AI-based image recognition technology for cancer detection has advanced rapidly in recent years, and several breast cancer models have U.S. Food and Drug Administration (FDA) approval.

The use of artificial intelligence (AI) has become more widespread and is experiencing widespread adoption in all industries. With increasing competitive pressures and observations of their peers' AI successes, more and more businesses are integrating AI into various aspects of their operations. The Machine Learning (ML) models that drive AI systems have become increasingly powerful, displaying superhuman abilities on most tasks. Although AI systems have increased in performance, model complexity has increased as well, making them a black box with decisions that may be difficult for humans to understand. As black box models influence not only business outcomes but also the lives of many people, they can have severe ramifications.

Artificial Intelligence, machine learning and predictive analytics are increasingly viewed as a matter of national security. Federal government IT experts expect that in 2022 and beyond, this trend will drive new policy initiatives and investments that could advance further development of these technologies. This will likely expand their application in the Defense Department and, to some extent, civilian agencies. Public federal spending on AI/ML rose to nearly $1 billion in fiscal year 2020 -- a 50 percent increase from fiscal year 2018 -- making it one of the fastest growing emerging technology investment areas, says Bill Wright, director of federal government affairs at Splunk. Earlier this year, the National Security Commission on Artificial Intelligence released its final report to Congress, urging more funding for AI/ML to better compete with China and others, Wright says.